The ReThink study: a 3-arm parallel randomized trial of cognitive bias modification, with and without adherence promotion, for adolescent anxiety disorder: trial design and protocol.

BACKGROUND: Anxiety disorders are the most common mental health problem among youth, contribute to reduced quality of daily life, and are associated with high rates of comorbidity. However, treatment rates for anxiety are very low, causing a sizeable treatment gap. There is an immediate need to identify treatment interventions that are effective, affordable, and can be delivered easily to the youth population. Cognitive Bias Modification (CBM) is one potentially effective intervention that could reach youth on a large scale, especially when self-administered at home. Thus, we aim to assess the benefit of CBM to treat youth anxiety. Further, we aim to test whether adding an adherence promotion (AP) component to the CBM intervention can improve outcomes, and whether CBM delivered both with and without the AP component is cost effective. METHODS: This is a 12-month randomized controlled trial (RCT) conducted within an existing healthcare system. Potentially eligible youth (ages 12 to 17) will be identified by reviewing the electronic health record (EHR) for clinical anxiety diagnoses, which are then confirmed via research interview. We aim to enroll 498 participants and randomize them 1:1:1 to one of three arms: Arm 1 is a Low-Ratio version of the CBM program (nearly identical to the other CBM versions, but minimally effective); Arm 2 is a High-Ratio "active" CBM program; and Arm 3 is the High-Ratio CBM program with an added AP component. Participants will complete assessments at baseline, 1-, 3-, 6- and 12-months post-baseline. Youth in all three arms will self-administer the CBM program at home and will be asked to complete twelve intervention sessions over a four-week period. Arm 3 participants (High-Ratio CBM + AP) will also receive up to four telephone calls from phone coaches during the intervention period to provide technical assistance, encouragement, and motivational enhancement to increase adherence. The primary clinical outcome will be anxiety remission at 6-month follow-up. DISCUSSION: This study protocol describes the method and design for an RCT to test whether self-administered CBM both with and without adherence promotion can be an effective at-home treatment for anxious youth. TRIAL REGISTRATION: ClinicalTrials.gov : NCT02156531, First Posted June 5, 2014.

Using Real-world Data for Decision Support: Recommendations from a Primary Care Provider Survey.

INTRODUCTION: The use of data from wearable sensors, smartphones, and apps holds promise as a clinical decision-making tool in health and mental health in primary care medicine. The aim of this study was to determine provider perspectives about the utility of these data for building digitally based decision-making tools. METHODS: This mixed quantitative and qualitative cross-sectional survey of a convenience sample of primary-care clinicians at Kaiser Permanente Northwest was conducted between April and July 2019 online via Institute for Translational Health Sciences' Research Electronic Data Capture. Study outcomes were 1) attitudes toward digital data, 2) willingness to use digital data to support clinical decision making, and 3) concerns and recommendations about implementing a digital tool for clinical decision making. RESULTS: This sample of 131 clinicians was largely white (n = 98) female (n = 91) physicians (n = 86). Although respondents (75.7%, n = 87) had a positive attitude toward using digital tools in their practice, 88 respondents (67.3%) voiced concerns about the possible lack of clinical utility, suspected difficulty in integration with clinical workflows, and worried about the potential burden placed on patients. Participants indicated that the accuracy of the data in detecting the need for treatment adjustments would need to be high and the tool should be clinically tested. CONCLUSIONS: Primary care providers find value in collecting real-world patient data to assist in clinical decision making, provided such information does not interfere with provider workflow or impose undue burden on patients. In addition, digital tools will need to demonstrate high accuracy, be able to integrate into current clinical workflows, and maintain the privacy and security of patients' data.